On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks

Maximilian Seitzer, Arash Tavakoli, Dimitrije Antic +1

Capturing aleatoric uncertainty is a critical part of many machine learning systems. In deep learning, a common approach to this end is to train a neural network to estimate the pa…